Next Article in Journal
Influence of Digital Accounting System Usage on SMEs Performance: The Moderating Effect of COVID-19
Previous Article in Journal
Smart Tourism Ecosystem: A New Dimension toward Sustainable Value Co-Creation
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Variation of UTCI with the Background of Climate Change and Its Implications for Tourism in a Complicated Climate Region in Western China

1
Key Laboratory of Ecohydrology of Inland River Basin, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
2
State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
3
University of Chinese Academy of Sciences, Beijing 100049, China
4
College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
5
China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences and Higher Education Commission (CAS-HEC), Islamabad 45320, Pakistan
6
United Front Department of Yunyan District Committee of the Communist Party of China, Guiyang 550001, China
*
Authors to whom correspondence should be addressed.
Sustainability 2022, 14(22), 15047; https://doi.org/10.3390/su142215047
Submission received: 12 October 2022 / Revised: 30 October 2022 / Accepted: 10 November 2022 / Published: 14 November 2022

Abstract

:
Tourism plays an important role in Kashgar’s socio-economic development. Climate change has a profound impact on the development of tourism. However, basic research on climate change and its impact on tourism remains insufficient in Kashgar. Using the atmospheric reanalysis data ERA5 and the universal thermal climate index (UTCI) model, climate change and climate comfort were evaluated from 1979 to 2018. The annual mean UTCI was −2.3 °C, i.e., at the coolish level, with moderate cold stress, illustrating that Kashgar’s tourism climate was weak. The obvious increase in the annual mean air temperature led to an obviously increased UTCI and a lengthened comfortable period, which provides possibilities to exploit an attractive climate and the potential for tourism. The poor climate conditions imply that the development of Kashgar’s tourism should depend more on the diversification and uniqueness of tourism products and the quality of tourism services. Therefore, the development of increased tourism products and the expansion of tourism regions, in the context of improving climate conditions, were focused on. We expect this case study to provide a reference for consumer travel decision-making and a necessary scientific basis for the planning and implementation of a tourism-based national promotional strategy in western China.

1. Introduction

As an increasingly important component of global economic development, the comprehensive contribution of tourism to sustainable economic and social development is becoming increasingly apparent. The latest annual research showed that travel and tourism represented 10.3% of global GDP (US$9.6 trillion) in 2019 [1]. As tourism has a strong comprehensiveness and sensitivity, changes in the external environment, such as the economy, politics, and natural disasters, often have a direct impact on it [2]. The COVID-19 epidemic swept the world in 2020, and new virus variants continued to emerge in 2021, causing global tourism to fall into a wide-spread and deep recession. The contribution of travel and tourism to GDP dropped to 3.7% and 3.8% in 2020 and 2021, respectively [1]. The variation of tourism’s contribution to the economy in China was basically similar to the rest of the world: domestic tourists reached 6.006 billion; the total contribution of tourism was USD 1.57 trillion, while the ratio of tourism to GDP was 11.05%; and tourism practitioners (79.87 million) accounted for 10.31% of the total number of practitioners in the country in 2019 [3]. Mainly affected by COVID-19, the number of domestic tourists was 2.879 billion (a 52.1% decline compared to 2019), and domestic tourism revenue was USD 0.31 trillion (a 61.1% decline compared to 2019) in 2020 [3]. In 2021, the domestic tourism increased by 62.6% (compared to 2020) but was still below expectations [3].
Climate change is bound to become one of the biggest challenges [4] and presents a profound systemic challenge for tourism worldwide [5,6]. Since the influence of climate change on tourism will be long-term, quantitative research has become a necessity [7]. The index method, demand model, and selection analysis are the main methods for assessment [8]. Solymosi et al. [9] reported that thermal stress days in Hungary increased 4.1% per year from 1973 to 2008. Eludoyin and Adelekan [10] pointed out that, compared to 1951–1980, the effective temperature in the northern, central, and southern coastal areas of Nigeria increased by about 2 °C from 1981 to 2009. The average apparent temperature in 31 major provincial capital cities in China increased by 1.75 °C, while spring was the most significantly increased season between 1955 and 2005 [11].
Climate comfort, the degree comfort of the human body with the surrounding thermal environment, is the most basic index to measure whether a region is suitable for tourism activities [12,13], tourist travel decisions, and the rational development of tourist destinations [14,15]. The evaluation of climate comfort (ECC) has a history of nearly a hundred years [16,17,18,19]. In the early stages, the results of direct measurements using instruments were usually used for the evaluation [16]. A few years later, Houghton et al. [20] proposed an iso-comfort line including two variables, i.e., temperature and humidity, and put forward the concept of the effective temperature index (ETI). This marked the point where research on ECC entered the stage of empirical models, which mainly included wind chill index (WCI) [21], predicted four-hour sweat rate (P4SR) [22], wet bulb globe temperature (WBGT) [23], temperature–humidity index (THI) [24], and so on (e.g., apparent temperature (AT) [25]). These empirical indicators were simple to calculate and easy to understand. However, their overly simple form reduced the accuracy of the results and could not meet the basic requirement of the correspondence between the index value and the human thermo-physiological state, which led to limitations in their application [26]. A reasonable ECC model must be based on the human body heat exchange mechanism and comprehensively consider the influence of various factors, such as environmental factors, human metabolism, respiration and heat dissipation, and clothing thermal resistance [27]. With the development of biometeorology and computer science, research on mechanistic models has attracted extensive attention. Fanger [12] proposed three conditions to satisfy a human comfort state and produced the famous thermal comfort equation, creating a precedent for the application of the heat balance model in human biometeorology. Based on the ETI, Gagge et al. [28] comprehensively considered different activity levels and the thermal resistance of clothing, and proposed the standard effective temperature model (SET). Li and Chi [29] produced a comprehensive climate tourism information scheme (CTIS), which integrates thermal comfort, aesthetics, and physical influencing factors, and which offered a more complete guide for tourists. Yao et al. [30] constructed a comprehensive climate comfort index model and analyzed the variation of climate comfort in Northwest China under climate warming. Guan et al. [31] found that the tourist climate comfort of Xinjiang generally showed a warmer trend in 1979–2018. Owing to their simple calculation, easy access to parameters, and relatively reasonable parameters, empirical models are the most widely used models for climate comfort evaluation in practical applications [32]. With the widespread integration of multiple disciplines, the universal thermal climate index (UTCI) was established [26]. At present, the applicability of UTCI has been verified by many studies. Blazejczyk et al. [17] found that the correlation between UTCI and the commonly used comfort indices such as ET, PET, SET*, and PMV reached more than 96%; furthermore, the UTCI was more sensitive to the temporal changes of meteorological elements than other comfort indices, reflecting the subtle differences in how the human body perceives weather changes. Research on climate comfort in China has indicated that the annual UTCI decreased with increased latitude and showed positive trends in northeastern China, while this was negative in southwestern China [33]. The UTCI has been proven to be suitable for various scales and various climates for tourism [14,34,35,36,37] and has shown a growing trend for theoretical research on ECC [38,39,40].
The rich natural resources and unique cultural environment provide a foundation for the development of tourism in Kashgar. Kashgar, located in the middle of the Eurasian continent, is a crucial transportation hub for cultural exchange, tourism, and economic trade between China and other countries in Central Asia, Southern Asia, and Western Asia. Kashgar has extremely rich natural resources, such as mountains, glaciers, snow, forests, lakes, grasslands, oases, deserts, animals, and plants. The Karakuri Lake, Golden Populus Euphratica National Forest Park, and Davakun Desert scenic areas were designated. In addition, Taklimakan Desert (the second largest mobile desert in the world, known as the “sea of death”), Muztagh Peak (known as the “father of the glaciers”), and Pamir Plateau (known as the “roof of the world”) attract large numbers of tourists. Kashgar is the birthplace of Xinjiang’s ethnic culture. The ethnic folk customs, culture and art, architectural style, and traditions are relatively well preserved. This integration of natural resources and human resources provides unique conditions for the development of tourism. Based on the advantages of many types of tourism resource, strong vitality, a high level of monopoly, and strong complementarity, Kashgar’s tourism occupies an important position in the international and domestic tourism market. In addition, tourism has become the backbone of promoting regional economic development and has the important function of tourism poverty alleviation. In 2019, the number of tourists was 15.17 million and the tourism revenue reached USD 2.1 billion (14.5% of the total prefecture GDP). Compared with the rapid growth of tourism, the inadequate tourism infrastructure, insufficient supply of tourism products, inadequate understanding of the policies, and poor quality of tourism management personnel are the main limiting factors for the development of tourism in Kashgar. The weak basic research on tourism is another factor. There have been few studies and research projects on Kashgar’s tourism, and the results are normally written in Chinese [41,42,43,44,45,46,47]. All these factors have a certain negative impact on the publicity and development of Kashgar’s tourism industry.
Kashgar belongs to the warm–temperate continental arid climate zone. Due to the complicated terrain, the meteorological conditions vary greatly. It is divided into five sub-climatic areas: the plain climatic area, desert climatic area, hilly climatic area, Pamir Plateau climatic area, and Kunlun Mountains climatic area. These sub-climatic areas are a miniature of Western China’s climate region. As mentioned above, climate change has had a profound impact on the region’s natural and socio-economic factors, such as tourism, and Kashgar is no exception. With the background of climate change, Kashgar’s warming rate is higher than China’s average warming rate, which objectively affects the temporal and spatial variation of the climate comfort period. Research concerning climate change has generally used observation data from the limited meteorological stations in Kashgar [48,49,50]. These meteorological stations are generally distributed at relatively low altitudes. The general climate change, especially in high mountainous areas, is not clear. As a result, how climate change affects regional tourism is ambiguous. Therefore, it is particularly important to carry out research on the temporal and spatial pattern of tourism climate comfort and its pattern of evolution, to provide the necessary basic understanding and a scientific reference for Kashgar’s tourism development and planning.
Aiming at the problems mentioned above, our main objectives in this article included: (1) to explore historical climate change using observed and re-analysed meteorological data; (2) to calculate climate comfort using re-analysis of meteorological data and the UTCI model, and to give a deep understanding of the spatial differences and seasonal changes of the comfort period and comfort areas; and (3) to reveal the impact of climate change on regional tourism and put forward corresponding suggestions for the development of tourism from the perspective of climate comfort, and also to propose corresponding adaptive solutions to climate change in a timely manner, with scientific and rational zoning. In recent years, affected by global warming, the regional tourism climate resources of different destinations have changed accordingly, which has also brought severe challenges to the tourism and vacation industry in various regions of China. Kashgar is a microcosm of western China. We expect that this case study of Kashgar can provide a reference for consumers for travel decision-making and provide the necessary scientific basis for the planning and implementation of a tourism-based national promotional strategy in western China.

2. Study Area

Kashgar is located in the southwest of the Xinjiang Uygur Autonomous Region, in the west of the People’s Republic of China and the central part of Eurasia (Figure 1a). It is bordered by the Taklimakan Desert to the east, Tajikistan to the west, and Afghanistan and Pakistan to the southwest. Kashgar covers an area of 162,000 km2. Its geographic coordinates are 71.39° E to 79.52° E, and 35.28° N to 40.16° N (Figure 1a).
Kashgar is surrounded by mountains (the Tianshan Mountains to the north, the Pamir Plateau to the west, Karakoram Mountains to the south) and the Taklimakan Desert to the east. The entire terrain is inclined from southwest to northeast, with a large altitude drop. The highest mountain in the region, Qogir Peak, is 8611 m a.s.l, while the lowest point is in Taklimakan Desert, at 1100 m a.s.l (Figure 1b). The annual mean air temperature (AMAT) is 11.7 °C. Due to the high mountains, moisture from the Indian Ocean and the Arctic Ocean cannot reach the area [51]. The annual mean precipitation is in the range of 55–72 mm. The Kashgar and Yarkant rivers, which originate from the mountainous area, with the water mainly from melted ice and snow, pass through and form two famous oases, i.e., Kashgar Oasis and Yarkand Oasis.
Tourism occupies a special place in the regional economy of Kashgar. In 2019, the Kashgar area had a population of 4.62 million, with a GDP of USD14.67 billion and a per capita GDP of USD 3175. The number of tourists was 15.17 million, and tourism contributed USD 2.1 billion (14.5% of the total prefecture GDP) in 2019. The development of tourism mainly stems from the rich and unique tourism resources and products. First, the unique location made it an important commercial port on the ancient Silk Road, the center of East-West traffic, and an important intersection point of East-West economics, culture, and civilization. Second, the diversity of landscape types has created rich tourism resources. The terrain, with high mountains, hills, plains, deserts, and scattered oases, is complex. Third, Kashgar has a recorded history of more than 2100 years, and Kashgar City is the principal national, historical, and cultural city in Xinjiang. The cultural heritage is unique and irreplaceable. Kashgar is the place with the most distinctive Uyghur national characteristics, and the place with the most complete preservation of Uyghur national characteristics and folk customs [42]. Distinctive Uyghur architecture, large-scale earthen buildings, original Uyghur ethnic customs, folk-style transportation developed under special circumstances, and handicrafts exhibit the colorful folk customs. The integration of natural resources and human resources provides unique conditions for the development of tourism.
Kashgar, on the whole, belongs to the warm temperate continental arid climate zone. Generally speaking, it has four distinct seasons, sufficient sunlight, large annual and daily temperature changes, low precipitation, strong evaporation potential, and a dry climate. Owing to the complicated landforms, climatic conditions differ greatly. To better understand the differences between areas, we divided it into five sub-climatic areas: the plain climatic area (PCA), hilly climatic area (HCA), desert climatic area (DCA), Pamirs Plateau climatic area (PPCA), and Kunlun Mountains climatic area (KMCA) (Figure 1c).

2.1. The Plain Climatic Area (PCA)

The PCA includes the vast alluvial plains in the northern and central parts of Kashgar. The annual average temperature is around 12 °C, and the annual precipitation is around 50–60 mm. The temperature increases rapidly in spring. The summer is long and hot, with a short period of very hot days. The autumn is short and the temperature drops rapidly. The winter is not cold, but the low-temperature period is long. Spring and summer are windy, with dusty weather or sandstorms. The temperature has been increasing recently. Since the 1990s, the warming trend has strengthened, especially for the minimum air temperature. The maximum temperature has shown a downward trend. The number of windy days has also shown a downward trend. For tourism, the climate changes seem to be heading in a positive direction.
Due to the sufficient light and great temperature difference between the day and night, the sweetness of melons and fruits is very high, attracting a large number of tourists. This area concentrates tourism resources on human resources, represented by the 5A-level scenic spot Ancient Kashgar City (AKC). The AKC occupies one-fifth of the area of Kashgar City and is one of the largest earthen buildings in the world. These earthen buildings combine the characteristics of the Han and Tang Dynasties, ancient Roman heritage, and the modern life of the Uyghur nation, and are of great historical significance and value.

2.2. The Hilly Climatic Area (HCA)

The HCA, with an altitude of 1500–3000 m a.s.l, is distributed in the middle part and the north edge of Kashgar. The annual average temperature is around 11 °C. The winter is long, while the summer is short. The annual precipitation is more than 70 mm, mainly concentrated in the summer. The HCR is an area suitable for farming and animal husbandry. The tourism resources focus on natural resources, represented by the 5A-level scenic spot Golden Populus Euphratica National Forest Park (GPENFP), which contains a vast natural Populus euphratica forest, the Yarkant River, and the flat and barren Gobi Desert on both sides of the river. The environmental difference formed by the Gobi desert and the lush oases represent the essence of this scenic area and the charm of the landscape.

2.3. The Desert Climatic Area (DCA)

The DCA is distributed in the southern and eastern part of Kashgar and belongs to the desert climate zone of the Taklimakan Desert. The annual average temperature is above 11 °C. The diurnal temperature difference reaches over 40 °C. The temperature changes drastically, with very cold winters and sweltering summers. The annual precipitation is below 40 mm, while evaporation reaches 2500–3000 mm. The dry climate of the desert preserves the many historical sites.
There are sprawling dunes, abrupt terrain, sandstorms that cover the sky in spring and summer, and Populus euphratica forests in the DCA. The majestic and harsh desert displays the original ecology and ancient culture and attracts tourists.

2.4. The Kunlun Mountains Climatic Area (KMCA)

The KMCA is in the middle and southern part of Kashgar and belongs to western part of the Kunlun Mountains. The average altitude is 5500 to 6000 m a.s.l. There are three peaks over 7000 m and seven peaks over 6000 m in this area. The average annual temperature is below 5 °C, while the highest mountain belt is −30 to −7.5 °C. Blocked by many mountains, the annual precipitation in the Karakashi Valley is only 25–30 mm, while near the snow line it is about 300 mm. The precipitation on the northern slope is greater than that on the southern slope. The main peaks form the center of the modern alpine glaciation and are covered with snow all year round.
The Muztagh Peak is representative of the regional tourism resources. In Uyghur, “muz” means ice, “tagh” means mountain, “ata” means father, and “Muztagh Ata” (Muztagh) is “father of ice”. There are 128 modern glaciers in this area, with a total area of 377.21 km2. Muztag Glacier Park is located at the foot of Muztagh Peak, with an average altitude of 5000 m. Visitors can see the majesty of glaciers, the colorful ice towers and ice caves, and the fragility and coldness of ice lakes. In addition, the strange mountains and rocks, exotic flowers and plants, and rare wild animals are elements that attract tourists.

2.5. The Pamirs Plateau Climatic Area (PPCA)

“Pamir” means “roof of the world” in Tajik. The plateau is 4000 to 7700 m a.s.l, with many peaks. Its high terrain consists of several groups of mountains, with broad valleys and basins between them. The natural landscape has obvious vertical changes. There are pastures and rivers on the plateau, and the valley is a habitable area. The snow-covered mountains are locations for mountaineering. The beautiful and remote Karakuri Lake (black lake) is located at the foot of Mount Muztagh. It has an alpine climate, with an annual average temperature below 5 °C, long and cold winters, and mild summers. Precipitation is mainly concentrated in spring and summer. There are many windy days, sufficient sunlight, strong radiation, and mostly sunny days.
The Pamir Plateau was historically called Congling, and it was the only passage to travel westward on the Silk Road in the Han Dynasty. Many famous Buddhists and travelers, such as Faxian (an eminent monk from the Western Jin Dynasty), Xuanzang (an eminent monk from the Tang Dynasty) and Marco Polo (a famous traveler from Venice, Italy) visited this place and left their footprints and legends here. The Pamir Tourism Scenic Spot (PTSS), a 5A-level scenic area known as the International Highland Style Tourist Destination, has rich and unique tourism resources, including the world-famous Stone City ruins, unique Tajik folk customs, the fascinating Jincaotan National Wetland Park, historic Silk Road culture, and rare and strange plateau creatures. To appreciate the long-standing Tajik folk culture, tourists can enjoy Tajik wedding customs, traditional Tajik folk songs, Tajik eagle dances, Tajik costumes, and other cultural heritage displays and various traditional handicrafts in the Tajik Folk Village.

3. Data and Methods

3.1. Data Sources

3.1.1. Observation Data

The “China Surface Climatic Daily Data Set” provided by the National Meteorological Information Center (http://www.nmic.cn/) (accessed on 5 July 2022) was used. Five National Basic Meteorological Observing Stations (NBMOS) and three National Reference Climatological Stations (NRCS) within Kashgar were involved. The data set includes daily average/maximum/minimum air temperature (°C), precipitation (mm), average wind speed (km/h), sunshine hours (h), average/minimum relative humidity (%), and other meteorological elements. The observation data were mainly used in the introduction to the study area.

3.1.2. Atmospheric Reanalysis Data

The atmospheric reanalysis data, ERA5, i.e., the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis data, which have the advantage of temporal and spatial integrity, were used to analyze the variations of comfort level in the study area. Using advanced modelling and data assimilation systems, ERA5 combines historical observations into global estimates. ERA5 provides hourly estimates of atmospheric, land, and oceanic climate variables. The dataset has been proven to have good applicability [52,53,54,55] and can be downloaded from the climate data storage of the ECMWF Copernicus Climate Change Service (C3S) (https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5) (accessed on 23 May 2022).
ERA5 DAILY provides aggregated values for each day for seven ERA5 climate reanalysis parameters. In this study, data including 2 m air temperature (Ta, °C), 10 m V-component of wind (Vv, m/s), 10 m U-component of wind (Vu, m/s), 2 m dew point temperature, precipitation, and total cloud coverage (N) were used to calculate the UTCI. The required meteorological elements have a spatial resolution of 0.1° × 0.1° and a temporal resolution of 1 h.

3.2. Methods

The Universal Thermal Climate Index (UTCI) was used to evaluate climate comfort. The UTCI is a six degree polynomial equation based on the theory of thermophysiological exchange [56]. UTCI is mainly composed of a Fiala multi-node model and an adaptive dressing model. The Fiala model simulates the process of heat exchange between the human body and the outside world [57]; the clothing of the dressing model changes according to the changes in the meteorological elements of the surrounding environment [58]. A reference environment was proposed, to translate climate impacts into a single value and promote the interpretation and understanding of UTCI [59]. The standard reference environment of the UTCI can be found in reference [60]. Since the humidity and wind speed in the UTCI reference environment are fixed, the corresponding relationship between the thermo-physiological response index calculated using the Fiala model and the dressing model and the air temperature in the reference environment can form a mathematical model. When the meteorological conditions in the actual environment cause a temperature corresponding to the thermo-physiological response index in the mathematical model, this is the UTCI. There is a certain deviation (offset), which depends on the actual 2 m air temperature, 2 m dew point temperature, 10 m wind speed, and the mean radiant temperature [56], between the UTCI and the temperature in the actual environment. The UTCI is expressed as:
UTCI = Ta + Offset(Ta, Tmrt, Va, Td) = f(Ta, Tr, Va, Td)
where Ta is the 2 m air temperature (°C);
Tmrt is the mean radiation temperature (°C) and is estimated using the MENEX model [61]:
Tmrt = [ Rprim + 0.5   Lg + 0.5   La 5.39 × 10 8 + ( 273 + t ) 4 ] 1 / 4 273
where Rprim is the solar radiation absorbed by a unclothed man; Lg is the long-wave radiation flux density (W/m2) of the surface, and La is the long-wave radiation flux density (W/m2) of the atmosphere. Lg and La can be calculated from the surface temperature Tg (°C) and the 2 m air temperature Ta (°C), respectively.
L g = 5.5 × 10 8 ( 273 + T g ) 4
L a = 5.5 × 10 8 ( 273 + T a ) 4
Va is the wind speed (m/s), which is the combination of two wind speeds: Vu (10 m U-component of wind) and Vv (10 m V-component of wind):
Va = Vu 2 + Vv 2
The bioklima2.6 software (Warsaw, Poland) was used to calculated UTCI. The temporal resolution of the data was 1 h, and the UTCI was calculated 24 times per day. The daily UTCI was the arithmetic average of the 24 values. The estimation period was from 1 January 1979 to 31 December 2018. According to the thermal physiological response of the human body, corresponding to the comfort standard of the model, and referring to existing research, the stress categories were divided into 10 categories (Table 1) [56].

4. Results

4.1. Regional Climate Change

The precision of precipitation in the reanalysis data is relatively poorer, especially in regions with few observation meteorological stations and in mountainous regions. In addition, less precipitation has less impact on tourism in Kashgar. Considering the above reasons, air temperature was considered in this climate change research.

4.1.1. Annual Variation of Regional Air Temperature

The annual mean air temperature (AMAT) was 3.4 °C from 1979 to 2018 in Kashgar. Regarding the spatial distribution, the AMAT of DCA (13.2 °C) and PCA (11.3 °C) in the north and east was much higher than that in KMCA (0.9 °C) and PPCA (−7.0 °C) in the southern and western high-altitude areas. The AMAT showed a decreasing trend from north to south and from east to west (Figure 2), which is opposite to the temperature distribution in China. Due to the influence of topography, the influence of altitude on the air temperature in the region is far greater than that of the latitude. As far as the interdecadal variation of AMAT is concerned, the regional AMAT in 1999–2018 was much higher than that in the first 20 years. It was noted that the AMAT exhibited a sharp increase in 1998. From then on, the AMAT was 0.80 °C higher than in the previous 20 years. Climate warming led to a change in snow and glacier resources. The glacier decreased at a shrinkage ratio of 12.19% of the total glacier area and the annual rate of 0.30 % a−1 from 1976 to 2016 [62].
The variation trend of the AMAT was generally increasing in Kashgar and its sub regions (Figure 2 and Table 1). The increase ratio was 0.31 °C·(10a)−1, indicating that the AMAT had increased 1.2 °C in the past 40 years in Kashgar (Figure 2). This increase ratio is consistent with the results of Xinjiang (0.30 °C·(10a)−1; [63]) and the arid region of Northwestern China (ARNC, 0.31 °C·(10a)−1; [64]), indicating that the air temperature variation in Kashgar was similar to the overall area of Xinjiang and ARNC. It was higher than either the national average (0.278 °C·(10a)−1; [65]) or the global average based on the Climatic Research Unit (CRU) gridded Time Series TS3.26 [66]. As for the sub-regions, the AMAT increase ratios of the relatively low-altitude areas, i.e., the PCA (0.39 °C·(10a)−1), DCA (0.34 °C·(10a)−1), and HCA (0.35 °C·(10a)−1), were much larger than those of the relatively low-altitude areas, such as the KMCA (0.30 °C·(10a)−1) and PPCA (0.22 °C·(10a)−1) in the southern and western high-altitude areas.

4.1.2. Seasonal Variation of Regional Air Temperature

The variation characteristics of the seasonal mean air temperature (SMAT) in Kashgar were analyzed (Figure 3). The mean temperatures in spring, summer, autumn, and winter were 5.0 °C, 14.8 °C, 3.5 °C, and −9.5 °C, respectively. The variations of SMAT in the four seasons showed a fluctuating increase, but to different extents. The maximum warming ratio (0.48 °C·(10a)−1) appeared in spring, followed by autumn (0.37 °C·(10a)−1). The warming ratios in summer (0.24 °C·(10a)−1) and winter (0.28 °C·(10a)−1) were, relatively, much smaller. The increase ratio of SMAT in spring and autumn exceeded the annual increase ratio (0.31 °C·(10a)−1), with significant increases of 1.9 °C and 1.5 °C, respectively. This indicates that the rise of air temperature was dominated by the spring and autumn in Kashgar. This is helpful for the development of tourism in the area.
The variations of SMAT in the five sub-regions also showed a trend of a fluctuating increase, but the range of increases varied greatly across seasons and sub-regions. Similarly to the situation in the whole Kashgar region, the increase ratios of the SMAT in spring were the largest, ranging from 0.29 °C·(10a)−1 to 0.68 °C·(10a)−1, of which PCA was the largest and PPCA was the smallest. The increase ratios of the SMAT in autumn varied from 0.28 °C·(10a)−1 to 0.47 °C·(10a)−1, among which DCA was the largest and PPCA was the smallest. It is worth noting that the increase ratios of KMCA and PPCA in winter were relatively larger, reaching 0.34 °C·(10a)−1 and 0.23 °C·(10a)−1, respectively. This indicates that winter plays an important role in the increase of mountain air temperatures. In addition, the increase ratios of the SMAT of DCA were nearly 0 °C (10a)−1, indicating that the mean air temperature maintained a relatively stable state in winter over the past 40 years.

4.2. Variation of UTCI and Climate Comfort

4.2.1. Annual Variation of UTCI and Climate Comfort

The annual mean UTCI was −2.3 °C from 1979 to 2018 in Kashgar. On the whole, the thermal perception was at the coolish level, with moderate cold stress. This was mainly due to the large regional mountain areas and the long duration of low air temperatures. The relatively strong wind speed accelerated the low UTCI values. The UTCI showed a decreasing trend from north to south and from east to west (Figure 4), which is similar to the distribution of air temperature. In the north and east, most areas of the PCA and DCA were cool, with slight cold stress, which is close to the comfortable grade. The HCA was cool, with slight cold stress. In the south, the UTCI values were negative, with the lowest value reaching −18 °C, which is a cold level with strong cold stress. Regarding the interdecadal variation, the regional UTCI in 1999–2018 was much higher than that in the first 20 years. In addition, the UTCI experienced a particularly sharp increase in 1998, since that year the UTCI was 0.90 °C higher than the previous 20 years. These low UTCI values illustrate that Kashgar’s climate is not advantageous for tourism. The development of tourism depends more on the diversification and uniqueness of tourism products and the quality of tourism services.
The spatial distribution of the UTCI varied greatly (Figure 4 and Figure 5). The UTCIs of the DCA (7.1 °C), PCA (5.5 °C), and HCA (0.6 °C) in relatively low-altitude areas was much higher than that in the KMCA (−5.0 °C) and PPCA (−12.4 °C) in the southern and western high-altitude areas. Thermal perceptions were at the cool level, with light cold stress, in the first three plain or hilly regions; while they were at the cool level, with moderate cold stress, in the latter two mountainous regions. The thermal perception was even close to the cold level, with strong cold stress, in the PPCA.
The UTCI in different regions showed significant positive increase trends from 1979 to 2018 (p < 0.01) in Kashgar (Figure 5). The increase ratio was 0.31 °C·(10a)−1, which equals the increase ratio of the air temperature, indicating that the UTCI increased 1.2 °C in the past 40 years in Kashgar (Figure 5). The UTCI fluctuated gradually at the beginning of 1990s, rose rapidly around 1998, and then showed a positive fluctuation trend. The HCA and PCA were the regions with the fastest increase ratios, of 0.41 °C·(10a)−1 and 0.40 °C·(10a)−1, respectively. Followed by the KMCA, which was equal to the value of the entire Kashgar. Relatively speaking, the increase ratios of the UTCI in the DCA and PPCA regions were lower, with average increase ratios of 0.29 °C·(10a)−1 and 0.22 °C·(10a)−1, respectively. In general, the increase of the UTCI was beneficial to Kashgar’s tourism.

4.2.2. Seasonal Variation of the UTCI and Climatic Comfort

The mean UTCI in spring, summer, autumn, and winter was −1.1 °C, 13.7 °C, −2.7 °C, and −18.9 °C, respectively (Figure 6). On the whole, the thermal perception was at the comfortable level, with no thermal stress in summer. While in spring and autumn, the thermal perception was at the coolish level, with moderate cold stress. Moreover, the thermal perception was at the cold level, with strong cold stress, in winter (Figure 6). The cool level represented a large percentage of spring and autumn, and only a small part of eastern the PPCA was cold. Many tourism activities can be carried out in these two seasons. In summer, the low-altitude areas were at the comfortable level, while most of the southern areas were at the cool level. This indicates that the summer is the best season for the tourism, and practice proves this statement. However, there are many levels of thermal perception in winter. The low-altitude areas were at the cool level, which is suitable for snow tourism.
The variations of the UTCI in the four seasons showed a fluctuating increase, but the extent the of increase was different in Kashgar (Figure 7). The maximum variation ratio (0.50 °C·(10a)−1) appeared in spring, followed by the autumn (0.33 °C·(10a)−1). The warming ratios in summer (0.26 °C·(10a)−1) and winter (0.17 °C·(10a)−1) were, relatively, much smaller. In the four seasons, the increase ratio of the UTCI in spring and autumn exceeded the annual increase ratio (0.31 °C·(10a)−1), with significant increases of 2.0 °C and 1.3 °C, respectively. This indicates that the increase of the UTCI was dominated by the spring and autumn in Kashgar.
The variations of the UTCI in the five sub-regions showed a fluctuating increasing trend, except for in winter in the DCA. The range of increase varied greatly among the seasons and sub-regions. Similarly to the situation in the overall Kashgar region, the increase ratios of the UTCI in spring were the largest, ranging from 0.30 °C·(10a)−1 to 0.63 °C·(10a)−1, of which the PCA and DCA were the largest and the KMCA was the smallest. The increase ratios of the UTCI in autumn varied from 0.09 °C·(10a)−1 to 0.51 °C·(10a)−1, among which the DCA was the largest and the PPCA was the smallest. It is worth noting that the increase ratios of the KMCA and PPCA in winter were relatively large, reaching 0.49 °C·(10a)−1 and 0.29 °C·(10a)−1, respectively.

4.2.3. Spatial Distribution of Average Days Perceived Using Thermal Perception

On the whole, the spatial distribution characteristics of the annual days at different perception levels were quite varied in Kashgar (Figure 8). Cold perception, which includes cool, coolish, cold, chilly, and freezing, plays a leading role. This encompassed most of the days of the year in the south areas and around a half the year in the north. The comfortable perception was also distributed throughout the year. It accounted for about another half year in the PCA, DCA, and southern HCA. The hot perception, which includes warm, hot, hottish, and torrid, was less distributed in Kashgar. There were around 21 days with UTCI values exceeding 26 °C in the PCA and DCA.
As for the sub-regions, the PPCA had a cold perception all year round; only a small region the northern was in a comfortable state for 30 days. The mountain area in the south of the KMCA was in a cold state all year round, while the northern valley area had a comfortable period of about 50 days. The HCA had 223 days of cold perception and 142 days of comfortable perception. The PCA and DCA had 167 days of cold perception, 177 days of comfortable, and 21 days of heat perception. Mountain tourism should make full use of the limited relatively climate comfortable seasons.

5. Discussion

The complicated climate types in Kashgar lead to very distinct and varied climate comfort levels in different seasons and regions, which is helpful for dispersing seasonal pressure at tourism destinations and for providing a scientific basis for the relevant government departments and tourism enterprises to formulate policies and plans. The calculation results of the UTCI showed that Kashgar has universal and sufficient climate resources for summer tourism, but they are inadequate for winter tourism throughout the whole region. For the sake of a full and balanced development of tourism, all regions need to fully consider the heterogeneity and competitiveness of climate conditions, to rationally layout and create different tourism destinations in the new round of tourism construction.
The increasing tourism climate comfort and the lengthening comfortable period provide possibilities to exploit different climate attractions and potentials. As mentioned above, the low UTCI value illustrates that Kashgar’s tourism climate is not advantageous. The development of tourism depends more on the diversification and uniqueness of tourism products and the quality of tourism services. Through an innovative product supply of “tourism + climate”, the potential tourism climate resources will be transformed into tourism superior resources, so as to create a unique tourism climate brand, meet the rigid needs of diversified tourism experiences, and better achieve the goals of tourism, to promote regional socio-economic development, rural revitalization, and poverty reduction. Therefore, the following discussion focuses on the development of increased tourism products and the expansion of tourism regions, in the context of bettering climate conditions.

5.1. Development of Featured Tourism Products to Meet the Needs of More Tourists

Although the Ancient Kashgar City, Zepujin Populus euphratica Park, Khunjerab Pass, Dawakun Lake, and other scenic spots (Figure 9) are well-known at home and abroad, due to various unfavorable factors, the regional tourism products are still at a low level of industrial development. All kinds of tourism products remain at the low level of tourism, and the tourism products that reflect the cultural connotations and ethnic elements comprise a very small percentage. A tourism brand that fully reflects the characteristics of Kashgar has not yet been created, and the creation of tourism products is obviously out of touch with the tourism market. The tourism infrastructure is seriously insufficient, which is mainly manifested in the low grade of tourism infrastructure: various scenic spots and cultural parks remain in a basic condition; cultural infrastructure such as museums, art galleries, cultural centers, and ethnic exhibitions that the highlight ethnic characteristics are lacking; and facilities have not been fully utilized. This leads to tourists in Kashgar seeing only a single perspective. The aims for cultural tourism, education, and on-the-spot experiences are not achieved.
Kashgar is rich in folk culture tourism resources. In their long-term production and culture, the people of all ethnic groups in Kashgar have created, not only material folk culture, but also a distinctive social folk culture and spiritual folk culture [45]. Folk cultural tourism has made great progress and promoted the development of tourism and the local economy in Kashgar. Nevertheless, various problems, such as insufficient expression of the ethnic characteristics contained in the tourism resources, blind development and excessive development of folk tourism resources, a lack of professional planning and design and a lack of folklore resources for tourists, and awareness of folk tourism resource protection, limit the overall development of folk tourism in Kashgar. At present, Kashgar has been listed as a national global tourism demonstration area. This is a good opportunity for the development of tourism. Relying on the development of the tourism industry, the continuous development and growth of transportation, catering, scenic spots, commerce, agriculture, and other industries can be realized. In the process of promoting global tourism, it is necessary to develop more cultural tourism products and improve the connotations of tourism in Kashgar. The key areas for tourism development include the core area of Silk Road culture and ethnic customs tourism, the Pamir Plateau Tajik tourism area, the Qogori peak alpine tourism area, the Taklimakan Desert tourism area, and the Populus Euphratica oasis pastoral cultural tourism area. The five major tourism areas are led by cultural tourism products and promoted by the high-quality development of vacation and experience tourism. The development of folk-custom tourism products in Kashgar can be considered regarding the innovation of national handicrafts, the development of national etiquette and festival customs, the daily life of ethic dress, and the exploration of ethic diet, to fully experience the cultural charm of local residents in tourism activities.

5.2. Creation of Belt of Ice-and-Snow Tourism (IST) under the Warming Climate Background

With the successful holding of the 2022 Winter Olympic Games and the strategy of “encouraging 300 million people to participate in winter sports”, ice and snow resources have gradually become an important way to meet the people’s growing demand for a better life in China. China’s IST has developed rapidly and become an emerging driving industry for winter tourism [67]. With the implementation of the strategy of “rejuvenating Xinjiang through tourism”, IST has become a strategic industry in Xinjiang, which can effectively make up for the shortcomings of Xinjiang’s winter tourism, and is one of the important keys in promoting the transformation and innovation of the tourism economic structure and to systematically drive the development of various advantageous industries [68].
The development of IST depends on high-quality ice and snow resources and suitable climatic and topographic conditions [69]. From November, the snow season in Karshgar lasts for about 4–5 months, with an average snow thickness of 15 cm (in the PCA, HCA, and DCA), 40 cm in mountainous area (KMCA and PPCA), and an average winter temperature of −5 °C to −15 °C in the PCA, HCA, and DCA. The long snow period, large snow volume, and good snow quality create an excellent natural basis for the development of IST. In addition, the unique geographical and geomorphic features, such as elevation, mountain drop, and slopes ensure the development of ice and snow sports such as skiing. Glaciers are widely distributed in the Pamirs, Karakorum, and Kunlun Mountains. In the eastern mountains of Pamirs, the total area of glaciers is more than 2200 km2. Among them, the glacier area of Gongger Muztagh Mountain is 635 km2, and the ice thickness is over 100 m. The Hoh Xil Glacier on the east slope of Muztagh, the Yangbulak Glacier on the northwest slope, and the Kela Ya Kela Glacier on the north slope of Gongger Mountain are over 20 km long, with magnificent and strange landscapes. In the Karakoram Mountains, the famous 40.2 km long Yinsuti Glacier is one of the largest glaciers in China. These glaciers provide Kashgar with relatively stable water resources and tourism resources. These special geological structures and ecological landforms, companied with the colorful folk culture tourism resources, endow Kashgar with unique attractions for IST, making it a popular new destination for national ice and snow tourism.
The development level of IST in Kashgar is relatively low and still in the primitive stage. Most of the ice and snow resources have not been effectively exploited as tourist attractions, as in other parts of the country [70]. Around Muztagh Peak, the only explored glacier tourism program focus only on sightseeing. Most ski resorts opened in 2021. Jinhuyang International Ski Resort, Yafuquan Jiangshan Ski Resort, and Dawakun Ski Resort (Figure 9) are the main destinations for skiing. Even under these poor conditions and the influence of COVID-19, Kashgar’s tourism industry, mainly the IST, received 3.06 million domestic tourists with an increase of 41.24%, and 1.75 billion RMB Yuan with an increase of 19.76%, in the first quarter of 2022. This fully demonstrates the development potential of IST.
Following the marketing strategy of “Silk Road Culture + Ethnic Customs + Ice and Snow Tourism”, Kashgar’s IST needs to be linked with the three current 5A scenic spots, Jinhuyang International Ski Resort, Yafuquan Jiangshan Ski Resort, and Dawakun Ski Resort, to create an ice and snow industry economic belt of “culture and sports + entertainment”. This joint product development effort is designed to leverage the advantages of ice and snow culture, history, human resources, and other aspects, in order to develop diversified ice and snow tourism experience projects. For example, competitive projects (such as sheep catching in the snow, ski racing, and snow wrestling) and special experience projects (such as an ice and snow fairy tale town and an ice and snow adventure town) are being developed from the ethic culture of ice and snow in these scenic areas. Ice and snow sports activities, which simultaneously meet the needs of leisure and entertainment, teaching and training, and event hosting, are being developed around ski resorts and glacier tourism areas. Further large-scale snow and ice sports activities, such as ski festivals and ice tourism festivals, are to be held in due time, to promote the formation of a snow and ice industry chain, integrating ice and snow sports, equipment manufacturing, and industrial services.
With the large increase of climate comfort in winter, the union of skiing, ice and snow parks, snow-sightseeing, entertainment and leisure, cultural experiences, and ethnic food is one of the main ways to develop IST in the area of HCA, PCA, and even the DCA. With the relaxation of tourism policy, the improvement of infrastructure, and the large increase of climate comfort, Kashgar needs to develop glacier tourism in the mountainous areas of PPCA and KLCA in summer. Aside from simple glacier sightseeing, programs such as skiing, glacier and snow expeditions, adventures by snow-mobile and helicopter, glacier and geology museums, and the full transformation of resource advantages into economic advantages must be considered [70].
Kashgar should make full use of the national ice and snow related policies, actively introduce ice and snow tourism support policies suitable for local development, and create a good policy environment for the development, investment, financing, and service supervision of IST destinations. As mentioned above, ice and snow tourist destinations are mostly in high mountain areas, with many types and a high frequency of natural disasters. In addition to the impact of global climate change, debris flows, floods, and other disasters caused by the melting of snow and glaciers frequently occur [71]. The IST destinations must establish a systematic disaster prevention, reduction, and relief mechanism and plan to improve the resilience of the IST destinations in the context of natural and human disasters [72]. The development and utilization of ice and snow resources should promote the rational protection of natural resources, strengthen the scientific protection and management regulation of resources, create a good natural ecological environment, and enhance the attractiveness to tourists.

5.3. The Possibility of the Construction of a Kashgar City-Tashkorgan Border Tourism Pilot Area (KTBTPA)

Border tourism refers to tourism activities in which an eligible travel agency can organize and receive citizens from China and neighboring countries to enter and leave from designated border ports in a team mode, and conduct tourism activities within the border area and a time limit agreed by the governments [73]. At present, from a regional point of view, the border tourism at the China–Vietnam border in Guangxi Zhuang Autonomous Region; China–Laos border, China–Myanmar border, and China–Vietnam border in Yunnan Province; China–Russia border in Heilongjiang Province; China–North Korea borders in Dandong, Liaoning Province, and Yanbian, Jilin Province; and China–Nepal, China–India, and China–Burea borders in Tibet are relatively better developed. Affected by harsh natural conditions and certain major events, border tourism in Xinjiang has been greatly restricted. With the improvement of tourism climatic conditions, traffic conditions and other infrastructure, and the relaxation of policies, the development of border tourism in Kashgar has great potential.
Kashgar City–Tashkorgan has good conditions and a solid basis for the construction of a border tourism pilot area. Kashgar City is central to the preservation and innovation of heritage stretching over two millennia, as a repository for “Uyghurness” [74,75]. Due to its importance in the development and opening up of China’s northwest frontier, Kashgar City has been classified as a state-level border city [76]. Adjacent to Pakistan, Khunjerab Pass, which is the highest (4733 m a.s.l) pass in the world and a national first-class pass, is the only land entry and exit channel between China and Pakistan. The Karakoram Highway from Kashgar to Khunjerab is 415 km long. Famous scenic spots such as Oytak Forest, Karakuri Lake, Muztagh Peak, Stone City, and Golden Grass Beach are on this route (Figure 9). In addition, KTBTPA (Figure 9) belongs to the regional cooperation frameworks such as “Belt and Road” and the China–Pakistan economic corridor. With the strengthened development of the Belt and Road Initiative and its construction towards the Xinjiang region, the conditions and infrastructure for building KTBTPA have been greatly changed. Together with the Ministry of Foreign Affairs, the Ministry of Public Security, the General Administration of Customs, the Immigration Bureau, and the Ministry of Culture and Tourism were responsible for the “Measures for the Administration of Border Tourism (Revised Draft for Comment)” on 19 September 2022 [76]. It is mentioned that the state encourages border areas to strengthen cooperation with border areas of neighboring countries, to promote the development of border tourism and create distinctive border tourism destinations. Some measures implemented include canceling border tourism project approval, relaxing border tourism controls, encouraging border areas to create distinctive border tourism destinations, and flexibly choosing ports of entry and exit.
The main goal of the construction of the KTBTPA is as follows: (1) to improve tourism infrastructure, so that border tourism becomes a new force in the economic development of the border area; (2) to cultivate a sound tourism industry system, so that border tourism can become a powerful booster for the prosperity of the border and the people; (3) through the proximity and driving effects of border tourism, the level of economic development and the living conditions of people in border areas will be comprehensively improved; the ethnic cultural customs, natural ecology, and social life in border areas will be protected and displayed; and social management in border areas will be optimized; (4) to gradually accumulate a basis and experience for a cross-border tourism cooperation zone, which will focus on promoting inferstructure and transformation, and upgrading the border tourism industry and services in the future.

5.4. The Possibility of the Development of Cross-Border Tourism

The vast geographical span, diversified cultural span, and long historical span of Kashgar region are rare advantages in the development of cross-border tourism. Located at the junction of Central Asia, the Indian subcontinent, and China, Kashgar has an 889 km border with Pakistan, Afghanistan, and Tajikistan, and is adjacent to India, Kyrgyzstan, Kazakhstan, Uzbekistan, and Turkmenistan. It is the most important land route connecting China with Central and South Asia, and a bridge linking the Pacific and Indian Oceans. Kashgar brings together the Chinese culture, Indian culture, Persian culture, and Arab culture, forming a distinctive national and totem culture. Five national first-class ports on the border, including Khunjerab, Turgat, Irkesh Tanzania, Karasu, and Kashgar International Airport, connect Central Asia, South Asia, and China together. Currently, it is an essential connectivity node for the Belt and Road Initiative (BRI), in addition to being a throughway for the China–Pakistan Economic Corridor, and it also connects to Kyrgyzstan via the Irkeshtam Range and Torugart passes. Accompanying the improvement of climate conditions, taking advantage of this location, with the help of natural resources and especially human resources, and making use of both domestic and foreign markets, Kashgar will develop in-depth cross-border tourism in future, as follows:
Under the Belt and Road Initiative, Chinese–Pakistani relations have been elevated to an all-weather strategic partnership. Due to the high similarity in cultural beliefs between ethnic minorities in Xinjiang and Pakistan, promoting cultural exchanges between China and Pakistan has become an important way to promote cooperation between the two countries. Therefore, as a node of the China–Pakistan Economic Corridor, the Kashgar area has deeply explored the culture of India and Pakistan, Central Asian culture, Silk Road culture, and Kashgar ethnic culture, etc., and established a cultural exchange park between China and Pakistan, so that the culture of this China–Pakistan friendship can be passed to the younger generation.
Kashgar should take Silk Road tourism as its main development direction. Initially, tourism will extend southward to Pakistan. Taking the China–Pakistan friendship and cultural tourism as the core, it is necessary to build a China–Pakistan Economic Corridor Tourism Alliance. Through tourism, visitors can deeply understand the nature resources and folk customs of both countries. Second, take the Wakhan Corridor culture as the main route and deeply the develop the various cultures of the Wakhan Corridor to the southwest. The Wakhan Corridor, also known as the Afghanistan Corridor and the Wakhan Pamir, is located in a valley between the southern end of the Pamir Plateau and the northeastern section of the Hindu Kush Mountains. It is an east–west narrow strip, stretching from the Islamic Republic of Afghanistan to Xinjiang, China. The Wakhan Corridor, connecting East Asia, Central Asia, West Asia, and South Asia together, is part of the ancient Silk Road and an important channel for the exchange between Chinese civilization and Indian civilization. Through tourism in Afghanistan and India, visitors can deeply understand Indian civilization. Third, set up joint tourism products of creative, scientific, and technological exploration, and make connections between the ethnic culture of China and the Central Asian countries.
Cross border tourism can expand the domestic and international tourism markets and strengthen the tourism supply. Relying on rich and exotic customs, green ecology, health preservation, and shopping, cross-border tourism can gradually develop new tourism business activities and projects. Tourism products have the characteristics of heterogeneous business types, complex industries, multilateral cooperation, and overlapping circles; greatly enriching tourism products, strengthening the tourism supply and incremental supply, and improving the variety and quality of supply. This can also stimulate consumption, enhance attractiveness, expand domestic and international tourism markets, build links between domestic and international markets, and realize the development of domestic and foreign markets.

6. Conclusions

Using the atmospheric reanalysis data ERA5, the historical variation of annual air temperature from 1981 to 2018 in Kashgar was analyzed. In addition, climate comfort and its spatiotemporal change in Kashgar were evaluated using the relevant meteorological elements combined with GIS spatial analysis technology, linear regression equations, and a universal thermal climate index (UTCI) model. Based on the UTCI results, some suggestions on promoting the development of tourism in Kashgar were put forward.
There were obviously increasing trends in the annual mean temperature from 1981 to 2020, in all regions in Kashgar. The warming climate led to an increase of the climate comfort, which was mainly beneficial for tourism, especially in high-latitude areas. Of course, some tourism resources, such as glaciers, are facing risks. An increase of natural hazards, such as floods, debris flows, and other disasters may increase the loss of the tourism facilities and even tourists’ lives and property.
The evaluation results of the climate comfort showed that the thermal perception was at the coolish level, with moderate cold stress, illustrating that Kashgar’s tourism climate is not advantageous. The evaluation results also implied that the low-altitude areas were more suitable for the development of tourism. Summer, autumn, and spring were the main seasons for tourism.
Although Kashgar has rich tourism resources, the development of tourism is largely dictated by the variety and uniqueness of tourism products and the quality of tourism services. Sightseeing tours are still the leading product in Kashgar. It is necessary to develop more cultural tourism products and improve the connotations of tourism through the development of high-quality vacation and experience tourism. The development of folk-custom tourism products in Kashgar can be considered, from the innovation of national handicrafts, the development of national etiquette and festival customs, the daily life of ethic dress, to the exploration of ethic diet. Following the marketing strategy of “Silk Road Culture + Ethnic Customs + Ice and Snow Tourism”, Kashgar has the conditions to create an ice and snow industry economic belt. Kashgar City–Tashkorgan has regional advantages, a solid basis, and policy opportunities for the construction of a border tourism pilot area. Relying on the rich and exotic customs, green ecology, health preservation, and shopping, cross-border tourism in Kashgar may gradually develop new business tourism activities and projects, in order to expand domestic and international tourism markets and strengthen the supply of tourism. Through the innovative product supply of “tourism+”, potential tourism resources will be transformed into superior tourism resources, to create a unique tourism brand, meet the needs of diversified tourism experiences, and better achieve the goals of tourism, in order to promote poverty reduction, revitalization, and economy development.
Research on the relationship between climate change and tourism is a mixed discipline and involves meteorology, tourism, economics, geography, physiology, geopolitics, and computing sciences. The calculation of climate comfort is a simple example. Therefore, researchers should use the power of science and technology, the integration of disciplines, and various qualitative and quantitative research methods to conduct research in the future, so as to actively address the impact of climate change on tourism and formulate coping strategies. An increasing frequency of extreme weather events and the outbreak of diseases caused by global warming and large-scale climate fluctuations have the most direct and severe impacts on tourism. These are the difficulties that tourism will encounter in adapting to climate change. How to mitigate the damage to tourism caused by climate change and how to use climate change to create opportunities for tourism development are becoming the focus of current research. The impact of climate change on tourism is multifaceted. The study of climate comfort is only a small part. More comprehensive research on the relationship between climate change and tourism is expected in the future.

Author Contributions

Conceptualization: J.W. and T.J.; methodology: T.J. and D.Z.; software: T.J. and D.Z.; data curation: T.J., Y.W. and Y.M.; writing—original draft preparation: J.W. and T.J.; writing—review and editing: J.W., T.J., Y.W., Y.M. and Y.D. All authors have read and agreed to the published version of the manuscript.

Funding

The research was funded by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA23060702 and XDA19070501); The Ministry of Science and Technology (Grant No. 2018FY100502).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article, the data presented in this study are available in Section 3.1.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. World Travel and Tourism Council. Travel & Tourism Economic Impact; WTTC: London, UK, 2022. [Google Scholar]
  2. Luthe, T.; Wyss, R. Assessing and planning resilience in tourism. Tour. Manag. 2014, 44, 161–163. [Google Scholar] [CrossRef]
  3. China Tourism Academy. Annual Report of China Domestic Tourism Development 2021; Tourism Education Press: Beijing, China, 2022; pp. 1–36. [Google Scholar]
  4. IPCC. AR6 Climate Change 2021: The Physical Science Basis; Sixth Assessment Report; IPCC: Geneva, Switzerland, 2021. [Google Scholar]
  5. Steiger, R.; Posch, E.; Tappeiner, G.; Walde, J. The impact of climate change on demand of ski tourism-a simulation study based on stated preferences. Ecol. Econ. 2020, 170, 106589. [Google Scholar] [CrossRef]
  6. WTM (World Travel Market). Why the ministers’ summit 2007 is crucial to the industry. In Proceedings of the UNWTO Ministers Summit on Tourism and Climate Change, London, UK, 13 November 2007. [Google Scholar]
  7. Rosselló-Nadal, J. How to evaluate the effects of climate change on tourism. Tour. Manag. 2014, 42, 334–340. [Google Scholar] [CrossRef]
  8. Zeng, Y.; Zhong, L.; Liu, H. Implications of overseas quantitative studies of climate change impact on tourism for domestic research. J. Nat. Resour. 2019, 34, 205–220. [Google Scholar] [CrossRef]
  9. Solymosi, N.; Torma, C.; Kern, A.; Maróti-Agóts, Á.; Barcza, Z.; Könyves, L.; Berke, O.; Reiczigel, J. Changing climate in Hungary and trends in the annual number of heat stress days. Int. J. Biometeorol. 2010, 54, 423–431. [Google Scholar] [CrossRef]
  10. Eludoyin, O.M.; Adelekan, I.O. The physiologic climate of Nigeria. Int. J. Biometeorol. 2013, 57, 241–264. [Google Scholar] [CrossRef]
  11. Yu, Y.; Zheng, Y.; Tan, J.; Wu, R.; Xu, X. Changes of physiological equivalent temperature of big cities in China during 1955–2005. Sci. Meteorol. Sin. 2009, 29, 272–276. [Google Scholar]
  12. Fanger, P.O. Thermal Comfort: Analysis and Applications in Environmental Engineering; Danish Technical: Copenhagen, Denmark, 1970. [Google Scholar]
  13. ASHRAE. ASHRAE Handbook: HVAC Systems and Equipment; American Society of Heating, Refrigerating and Air-Conditioning Engineers: Atlanta, GA, USA, 2000. [Google Scholar]
  14. Ge, Q.; Kong, Q.; Xi, J.; Zheng, J. Application of UTCI in China from tourism perspective. Theor. Appl. Climatol. 2016, 128, 551–561. [Google Scholar] [CrossRef]
  15. Rutty, M.; Scott, D.; Matthews, L.; Burrowes, R.; Trotman, A.; Mahon, R.; Charles, A. An Inter (HCI: Beach) and the tourism climate index (TCI) to explain Canadian tourism arrivals to the Caribbean. Atmosphere 2020, 11, 412. [Google Scholar] [CrossRef] [Green Version]
  16. Hill, L.; Griffith, O.W.; Flack, M. The measurement of the rate of heat loss at body temperature by convection, radiation and evaporation. Philos. Trans. R. Soc. B 1916, 207, 183–220. [Google Scholar]
  17. Blazejczyk, K.; Epstein, Y.; Jendritzky, G.; Staiger, H.; Tinz, B. Comparison of UTCI to selected thermal indices. Int. J. Biometeorol. 2012, 56, 515–535. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Yan, Y.; Yue, S.; Liu, X.; Wang, D.; Chen, H. Advances in assessment of bioclimatic comfort conditions at home and abroad. Adv. Earth Sci. 2013, 28, 1119–1125. [Google Scholar]
  19. Matzarakis, A.; Fröhlich, D. Sport events and climate for visitors—The case of FIFA World Cup in Qatar 2022. Int. J. Biometeorol. 2015, 59, 481–486. [Google Scholar] [CrossRef] [PubMed]
  20. Houghton, F.C.; Yaglou, C.P. Determining Equal Comfort Lines. J. Am. Soc. 1923, 29, 165–176. [Google Scholar]
  21. Major, P.; Siple, A.; Charles, F. Measurements of dry atmospheric cooling in subfreezing temperatures. Proc. Am. Philos. Soc. 1945, 89, 177–199. [Google Scholar]
  22. McArdle, B.; Dunham, W.; Holling, H.E.; Ladell, W.S.S.; Scott, J.W.; Thomson, M.L.; Weiner, J.S. The Prediction of the Physiological Effects of Warm and Hot Environments/Renewable Northwest Project Report 47/391; Medical Resource Council: London, UK, 1947. [Google Scholar]
  23. Yaglou, C.P.; Minard, D. Control of heat casualties at military training centers. Arch. Ind. Health 1957, 16, 302–316. [Google Scholar]
  24. Thom, H. A new concept for cooling degree days. Air Cond. Heat. Vent. 1957, 54, 73–80. [Google Scholar]
  25. Steadman, R.G. The assessment of sultriness. Part I: A temperature-humidity index based on human physiology and clothing science. J. Appl. Meteorol. 1979, 18, 861–873. [Google Scholar] [CrossRef]
  26. Jendritzky, G.; de Dear, R.; Havenith, G. UTCI: Why another thermal index? Int. J. Biometeorol. 2012, 56, 421–428. [Google Scholar] [CrossRef] [Green Version]
  27. Parsons, K.C. Human Thermal Environments: The Effects of Hot, Moderate, and Cold Environments on Human Health, Comfort and Performance; Taylor & Francis: London, UK, 2003. [Google Scholar]
  28. Gagge, A.P.; Stolwijk, J.A.J.; Nishi, Y. An effective temperature scale based on a simple model of human physiological regulatory response. ASHRAE Trans. 1971, 77, 247–272. [Google Scholar]
  29. Li, R.; Chi, X.L. Thermal comfort and tourism climate changes in the Qinghai-Tibet Plateau in the last 50 years. Theor. Appl. Climatol. 2014, 117, 613–624. [Google Scholar] [CrossRef]
  30. Yao, X.; Zhang, M.; Zhang, Y.; Xiao, H.; Wang, J. Research on evaluation of climate comfort in Northwest China under climate change. Sustainability 2021, 13, 10111. [Google Scholar] [CrossRef]
  31. Guan, J.; Li, D.; Xu, X.; Wang, Y.; Wang, X. Spatiotemporal pattern and evolution of tourism climate comfort period in Xinjiang in recent 40 years. J. Southwest Univ. 2022, 44, 185–197. [Google Scholar]
  32. Sun, M.; Li, S. An empirical model for climate comfort evaluation: Review and prospect. J. Tour. 2015, 30, 19–34. [Google Scholar]
  33. Kong, Q.; Zheng, J.; Wang, X. Spatial pattern and temporal variation in thermal comfort in China from 1979 to 2014. Resour. Sci. 2016, 38, 1129–1139. [Google Scholar]
  34. Bröde, P.; Blazejczyk, K.; Fiala, D.; Havenith, G.; Holmér, I.; Jendritzky, G.; Kuklane, K.; Kampmann, B. The universal thermal climate index UTCI compared to ergonomics standards for assessing the thermal environment. Ind. Health 2013, 51, 16–24. [Google Scholar]
  35. Pappenberger, F.; Jendritzky, G.; Staiger, H.; Dutra, E.; Di Giuseppe, F.; Richardson, D.S.; Cloke, H.L. Global forecasting of thermal health hazards: The skill of probabilistic predictions of the Universal Thermal Climate Index (UTCI). Int. J. Biometeorol. 2015, 59, 311–323. [Google Scholar] [CrossRef] [Green Version]
  36. Zeng, D.; Wu, J.; Mu, Y.; Deng, M.; Wei, Y.; Sun, W. Spatial-temporal pattern changes of UTCI in the China-Pakistan economic corridor in recent 40 years. Atmosphere 2020, 11, 858. [Google Scholar] [CrossRef]
  37. Lin, H.; Ma, H.; Zhang, M. Analysis of the variation characteristics of human thermal comfort in summer of China from 1980 to 2019 based on UTCI. Clim. Chang. Res. 2022, 18, 58–69. [Google Scholar]
  38. Matzarakis, A.; Rammelberg, J.; Junk, J. Assessment of thermal bioclimate and tourism climate potential for central Europe-the example of Luxembourg. Theor. Appl. Climatol. 2013, 114, 193–202. [Google Scholar] [CrossRef]
  39. Chi, X.; Li, R.; Cubasch, U.; Cao, W. The thermal comfort and its changes in the 31 provincial capital cities of mainland China in the past 30 years. Theor. Appl. Climatol. 2018, 132, 599–619. [Google Scholar] [CrossRef]
  40. Zeng, D.; Wu, J.; Mu, Y.; Li, H.; Deng, M.; Wei, Y.; Sun, W. An assessment of tourism climate comfort in the China-Pakistan Economic Corridor. Sustainability 2020, 12, 6981. [Google Scholar] [CrossRef]
  41. Sun, Y. Status Analysis on tourism of Kashgar and its optimizing policy. Heilongjiang Agric. Sci. 2011, 2, 127–130. [Google Scholar]
  42. Zhang, N.; Song, J.; Jiang, Y.; Li, M. Evaluation of tourism resources of the Kashgar and analysis of the developing measures. J. Arid. Land Resour. Environ. 2011, 25, 178–182. [Google Scholar]
  43. Jia, Q.; Mamuti, M.; Aierxiding, Y. A Study on residents’ perception on tourism impact in the minority historical and cultural city of Kashgar. J. Beifang Univ. Natl. 2012, 5, 93–100. [Google Scholar]
  44. Pu, Y.; Yang, Z.; Han, F. Evaluation of development models for ethnic cultural tourism in Kashgar City, Xinjiang. Arid. Land Geogr. 2012, 35, 309–316. [Google Scholar]
  45. Guo, H. Countermeasures for the Development of Folk Custom Tourism in Kashi region of Xinjiang. Econ. Res. Guide 2018, 23, 100–103. [Google Scholar]
  46. Mamuti, M.; Liang, Z.; Wang, H. Research on the development path of Kashgar cultural tourism products under the “Belt and Road” initiative. J. Kashi Univ. 2020, 41, 23–29. [Google Scholar]
  47. Talif, Q. Research on the integration of tourism and urbanization in kashgar region. Shanghai Bus. 2021, 8, 139–141. [Google Scholar]
  48. Abudokerimu, A.; Qin, R.; Yillidarjiang, T.; Xin, Z. Climatic Variation Characteristics in Kashi Region during 1961–2010. Desert Oasis Meteorol. 2012, 6, 34–40. [Google Scholar]
  49. Kang, L.; Batur, B.; Luo, N.; Xue, Y.; Wang, M. Spatial-temporal Variations of Temperature and Precipitation in Xinjiang from 1961 to 2013. Xinjiang Agric. Sci. 2018, 55, 123–133. [Google Scholar]
  50. Erkejan, H.; Ajigui, S.; Mamtiali, M.; Apal, R. Study on temporal and spatial distribution characteristics of seasonal variation of air temperature in Xinjiang. Hubei Agric. Sci. 2022, 61, 25–33. [Google Scholar]
  51. Li, J.; Lei, J.; Li, S.; Yang, Z.; Tong, Y.; Zhang, S.; Duan, Z. Spatiotemporal analysis of the relationship between urbanization and the eco-environment in the Kashgar metropolitan area, China. Ecol. Indic. 2022, 135, 108524. [Google Scholar] [CrossRef]
  52. Meng, X.; Guo, J.; Han, Y. Preliminarily assessment of ERA5 reanalysis data. J. Mar. Meteorol. 2018, 38, 91–99. [Google Scholar]
  53. Napoli, C.D.; Barnard, C.; Prudhomme, C.; Cloke, H.L.; Pappenberger, F. ERA5-HEAT: A global gridded historical dataset of human thermal comfort indices from climate reanalysis. Geosci. Data J. 2020, 8, 1–9. [Google Scholar] [CrossRef]
  54. Sun, W.; Gao, X. Geomorphology of sand dunes in the Taklamakan Desert based on ERA5 reanalysis data. J. Arid Environ. 2022, 207, 104848. [Google Scholar] [CrossRef]
  55. He, Y.; Chen, C.; Li, B.; Zhang, Z. Prediction of near-surface air temperature in glacier regions using ERA5 data and the random forest regression method. Remote Sens. Appl. Soc. Environ. 2022, 28, 100824. [Google Scholar]
  56. Bröde, P.; Fiala, D.; Błażejczyk, K.; Holmér, I.; Jendritzky, G.; Kampmann, B.; Tinz, B.; Havenith, G. Deriving the operational procedure for the Universal Thermal Climate Index (UTCI). Int. J. Biometeorol. 2012, 56, 481–494. [Google Scholar] [CrossRef] [Green Version]
  57. Fiala, D.; Havenith, G.; Bröde, P.; Kampmann, B.; Jendritzky, G. UTCI-Fiala multi-node model of human heat transfer and temperature regulation. Int. J. Biometeorol. 2012, 56, 429–441. [Google Scholar] [CrossRef] [Green Version]
  58. Havenith, G.; Fiala, D.; Błazejczyk, K.; Richards, M.; Bröde, P.; Holmér, I.; Rintamaki, H.; Benshabat, Y.; Jendritzky, G. The UTCI-clothing model. Int. J. Biometeorol. 2012, 56, 461–470. [Google Scholar] [CrossRef] [Green Version]
  59. Pantavou, K.; Theoharatos, G.; Mavrakis, A.; Santamouris, M. Evaluating thermal comfort conditions and health response during an extremely hot summer in Athens. Build. Environ. 2011, 46, 339–344. [Google Scholar] [CrossRef]
  60. Stolwijk, J. A Mathematical Model of Physiological Temperature Regulation in Man; National Aeronautics and Space Administration: Washington, DC, USA, 1971. [Google Scholar]
  61. Matzarakis, A.; Rutz, F.; Mayer, H. Modelling radiation fluxes in simple and complex environments: Basics of the Ray Man model. Int. J. Biometeorol. 2010, 54, 131–139. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Hu, F. Remote Sensing Monitoring of Glacier Changes between Eastern Pamirs Plateau and Western Kunlun Mountains from 1976 to 2016. Master’s Thesis, Lanzhou University, Lanzhou, China, 2018. [Google Scholar]
  63. Drafting Committee of Xinjiang regional climate change assessment report 2020. Xinjiang Regional Climate Change Assessment Report: 2020 (Abstract for Decision-Makers); Meteorological Publishing House: Beijing, China, 2021; p. 22. [Google Scholar]
  64. Chen, Y.; Zhang, X.; Fang, G.; Li, Z.; Wang, F.; Qin, J.; Sun, F. Potential risks and challenges of climate change in the arid region of northwestern China. Reg. Sustain. 2020, 1, 20–30. [Google Scholar] [CrossRef]
  65. Zhao, D.; Gao, X.; Wu, S.; Zheng, D. Trend of climate variation in China from 1960 to 2018 based on natural regionalization. Adv. Earth Sci. 2020, 35, 750–760. [Google Scholar]
  66. Harris, I.; Jones, P. CRU TS3.26: Climatic Research Unit (CRU) Time-Series (TS) Version 3.26 of High-Resolution Gridded Data of Month-By-Month Variation in Climate. Centre for Environmental Data Analysis. 1 March 2019. Available online: https://doi.org/10.5285/7ad889f2cc1647efba7e6a356098e4f3 (accessed on 3 September 2022).
  67. Tang, C.; Xu, S. Sustainable Development of Ice and Snow Tourism—Theory & Empirical Studies: Preface. J. Resour. Ecol. 2022, 13, 547–551. [Google Scholar]
  68. Fan, D. SWOT analysis and countermeasure research on the development of ice and snow tourism in Xinjiang. Liaoning Sport. Sci. Technol. 2019, 3, 23–26. [Google Scholar]
  69. Zhang, X.; Zhang, Z.; Liu, L. Appraisement research on the suitability of ice and snow tourism resources in Xinjiang. J. Earth Inf. Sci. 2018, 11, 4–12. [Google Scholar]
  70. Wang, S.; Xie, J.; Zhou, L. China’s glacier tourism: Potential evaluation and spatial planning. J. Destin. Mark. Manag. 2020, 18, 100506. [Google Scholar]
  71. Jiang, C. Review and Prospect of China’s Ice-Snow Tourism Research in Recent 20 Years. Front. Soc. Sci. Technol. 2020, 2, 55–56. [Google Scholar]
  72. Jiang, Y.; Zhang, Y.; Gao, J.; Zhang, Y.; Fang, Y. High-quality development of ice and snow resources in China: Theoretical review, practice turn and challenge response. J. Nat. Resour. 2022, 37, 2334–2347. [Google Scholar] [CrossRef]
  73. Ming, Q. Research on Development Strategy and Policy Innovation of Land Border Tourism; Science Press: Beijing, China, 2022; p. 26. [Google Scholar]
  74. Mackerras, C. Kashgar, oasis city on China’s Old Silk Road. Asian Ethn. 2011, 12, 121–122. [Google Scholar] [CrossRef]
  75. Szadziewski, H.; Mostafanezhad, M.; Murton, G. Territorialization on tour: The tourist gaze along the Silk Road Economic Belt in Kashgar, China. Geoforum 2022, 128, 135–147. [Google Scholar] [CrossRef]
  76. Gao, J.; Ryan, C.; Zhang, C.; Cui, J. The evolution of Chinese border tourism policies: An intergovernmental perspective on border tourism in Xishuangbanna. Asia Pac. J. Tour. Res. 2022, 27, 157–172. [Google Scholar] [CrossRef]
Figure 1. Sketch map of Kashgar in Xiangjiang, China (a), topography (b), and sub climatic areas (c).
Figure 1. Sketch map of Kashgar in Xiangjiang, China (a), topography (b), and sub climatic areas (c).
Sustainability 14 15047 g001
Figure 2. The variation of annual mean air temperature (left) and the variation ratios (right) from 1979 to 2018 in different areas in Kashgar.
Figure 2. The variation of annual mean air temperature (left) and the variation ratios (right) from 1979 to 2018 in different areas in Kashgar.
Sustainability 14 15047 g002
Figure 3. The variation of seasonal mean air temperature (left), and the variation ratio (right) from 1979 to 2018 in different areas in Kashgar.
Figure 3. The variation of seasonal mean air temperature (left), and the variation ratio (right) from 1979 to 2018 in different areas in Kashgar.
Sustainability 14 15047 g003
Figure 4. The distribution of annual mean UTCI from 1979 to 2018 in different areas in Kashgar.
Figure 4. The distribution of annual mean UTCI from 1979 to 2018 in different areas in Kashgar.
Sustainability 14 15047 g004
Figure 5. The variation of annual mean UTCI (left) and the variation ratios (right) from 1979 to 2018 in different areas in Kashgar.
Figure 5. The variation of annual mean UTCI (left) and the variation ratios (right) from 1979 to 2018 in different areas in Kashgar.
Sustainability 14 15047 g005
Figure 6. The distribution of the seasonal mean UTCI from 1979 to 2018 in different areas in Kashgar. (ad) The mean UTCI in spring, summer, autumn, and winter was −1.1 °C, 13.7 °C, −2.7 °C, and −18.9 °C, respectively.
Figure 6. The distribution of the seasonal mean UTCI from 1979 to 2018 in different areas in Kashgar. (ad) The mean UTCI in spring, summer, autumn, and winter was −1.1 °C, 13.7 °C, −2.7 °C, and −18.9 °C, respectively.
Sustainability 14 15047 g006
Figure 7. The variation of the seasonal mean UTCI (left) and the variation ratios (right) from 1979 to 2018 in different areas in Kashgar.
Figure 7. The variation of the seasonal mean UTCI (left) and the variation ratios (right) from 1979 to 2018 in different areas in Kashgar.
Sustainability 14 15047 g007
Figure 8. The spatial distribution of average days perceived by the cold perception (a), comfortable perception (b) and hot perception (c) from1979 to 2018 in different areas in Kashgar.
Figure 8. The spatial distribution of average days perceived by the cold perception (a), comfortable perception (b) and hot perception (c) from1979 to 2018 in different areas in Kashgar.
Sustainability 14 15047 g008
Figure 9. The distribution of the main scenic spots, scenic areas, and planned areas for tourism development. (SRCECTA, Silk Road culture and ethnic customs tourism; PPTTA, the Pamir Plateau Tajik tourism area; QPATA, the Qogori peak alpine tourism area; TDTA, the Taklimakan Desert tourism area; PEOPCTA, the Populus Euphratica oasis pastoral cultural tourism area; KTBTPA, Kashgar City-Tashkorgan border tourism pilot area).
Figure 9. The distribution of the main scenic spots, scenic areas, and planned areas for tourism development. (SRCECTA, Silk Road culture and ethnic customs tourism; PPTTA, the Pamir Plateau Tajik tourism area; QPATA, the Qogori peak alpine tourism area; TDTA, the Taklimakan Desert tourism area; PEOPCTA, the Populus Euphratica oasis pastoral cultural tourism area; KTBTPA, Kashgar City-Tashkorgan border tourism pilot area).
Sustainability 14 15047 g009
Table 1. UTCI equivalent temperatures categorized in terms of thermal stress and thermal perception.
Table 1. UTCI equivalent temperatures categorized in terms of thermal stress and thermal perception.
UTCI (°C)Stress CategoryThermal Perception
>46Extreme heat stressTorrid
38~46Very strong heat stressHottish
32~38Strong heat stressHot
26~32Moderate heat stressWarm
9~26No thermal stressComfortable
0~9Slight cold stressCool
−13~0Moderate cold stressCoolish
−27~−13Strong cold stressCold
−40~−27Very strong cold stressChilly
<−40Extreme cold stressFreezing
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Wu, J.; Jin, T.; Wu, Y.; Ding, Y.; Mu, Y.; Zeng, D. The Variation of UTCI with the Background of Climate Change and Its Implications for Tourism in a Complicated Climate Region in Western China. Sustainability 2022, 14, 15047. https://doi.org/10.3390/su142215047

AMA Style

Wu J, Jin T, Wu Y, Ding Y, Mu Y, Zeng D. The Variation of UTCI with the Background of Climate Change and Its Implications for Tourism in a Complicated Climate Region in Western China. Sustainability. 2022; 14(22):15047. https://doi.org/10.3390/su142215047

Chicago/Turabian Style

Wu, Jinkui, Tian Jin, Yancong Wu, Yongjian Ding, Yaqiong Mu, and Di Zeng. 2022. "The Variation of UTCI with the Background of Climate Change and Its Implications for Tourism in a Complicated Climate Region in Western China" Sustainability 14, no. 22: 15047. https://doi.org/10.3390/su142215047

APA Style

Wu, J., Jin, T., Wu, Y., Ding, Y., Mu, Y., & Zeng, D. (2022). The Variation of UTCI with the Background of Climate Change and Its Implications for Tourism in a Complicated Climate Region in Western China. Sustainability, 14(22), 15047. https://doi.org/10.3390/su142215047

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop